code: def _convertSavedModel(
      self,
      saved_model_dir,
      input_arrays=None,
      input_shapes=None,
      output_arrays=None,
      tag_set=None,
      signature_key=None,
  ):
      if tag_set is None:
          tag_set = set([tag_constants.SERVING])
      if signature_key is None:
          signature_key = (
              signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY
          )
      (
          graph_def,
          in_tensors,
          out_tensors,
          _,
      ) = convert_saved_model.freeze_saved_model(
          saved_model_dir=saved_model_dir,
          input_arrays=input_arrays,
          input_shapes=input_shapes,
          output_arrays=output_arrays,
          tag_set=tag_set,
          signature_key=signature_key,
      )
      return graph_def, in_tensors, out_tensors
  
imports: import os
  from tensorflow.lite.python import convert_saved_model
  from tensorflow.python.client import session
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.platform import test
  from tensorflow.python.saved_model import saved_model
  from tensorflow.python.saved_model import signature_constants
  from tensorflow.python.saved_model import tag_constants
label_desc: Use image node_id 5 for calling the FreezeSavedModelTest obj's underlying member method code with example usage: obj._convertSavedModel(saved_model_dir, input_arrays, input_shapes, output_arrays, tag_set, signature_key) and returns: graph_def,  in_tensors,  out_tensors